{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "13d83b59-57f7-48ee-8bff-deda7d28edc5",
   "metadata": {
    "tags": []
   },
   "source": [
    "\n",
    "# Max Clique Problem\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6d56bb6d-9f3b-45db-8e98-b50f27af7505",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Background\n",
    "\n",
    "The problem is in graph theory. A clique is a subset of vertices in a graph such each pair of them is adjacent to each other.\n",
    "\n",
    "The max clique problem is given a graph $G = (V,E)$, find the maximal clique in the graph. It is known to be in the NP-hard complexity class.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3b5fbdb8-373b-4629-8ca1-51ef9be82edd",
   "metadata": {},
   "source": [
    "# Solving the problem with classiq"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0bdc4e6a-199b-44b3-bd3f-fd24722b616b",
   "metadata": {},
   "source": [
    "## Define the optimization problem\n",
    "\n",
    "We encode each node"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "83ddbd07-f7ab-4d80-b357-3890622d395f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-07T15:48:19.815355Z",
     "iopub.status.busy": "2024-05-07T15:48:19.814727Z",
     "iopub.status.idle": "2024-05-07T15:48:20.366172Z",
     "shell.execute_reply": "2024-05-07T15:48:20.365339Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "import networkx as nx\n",
    "import numpy as np\n",
    "import pyomo.environ as pyo\n",
    "\n",
    "\n",
    "def define_max_clique_model(graph):\n",
    "    model = pyo.ConcreteModel()\n",
    "\n",
    "    # each x_i states if node i belongs to the cliques\n",
    "    model.x = pyo.Var(graph.nodes, domain=pyo.Binary)\n",
    "    x_variables = np.array(list(model.x.values()))\n",
    "\n",
    "    # define the complement adjacency matrix as the matrix where 1 exists for each non-existing edge\n",
    "    adjacency_matrix = nx.convert_matrix.to_numpy_array(graph, nonedge=0)\n",
    "    complement_adjacency_matrix = (\n",
    "        1\n",
    "        - nx.convert_matrix.to_numpy_array(graph, nonedge=0)\n",
    "        - np.identity(len(model.x))\n",
    "    )\n",
    "\n",
    "    # constraint that 2 nodes without edge in the graph cannot be chosen together\n",
    "    model.clique_constraint = pyo.Constraint(\n",
    "        expr=x_variables @ complement_adjacency_matrix @ x_variables == 0\n",
    "    )\n",
    "\n",
    "    # maximize the number of nodes in the chosen clique\n",
    "    model.value = pyo.Objective(expr=sum(x_variables), sense=pyo.maximize)\n",
    "\n",
    "    return model"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3496c5d6-7df6-49fb-b5b9-5ba48d2b7d62",
   "metadata": {},
   "source": [
    "### Initialize the model with parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "bc9871c1-224e-4206-b39e-af7e448aca70",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-07T15:48:20.372542Z",
     "iopub.status.busy": "2024-05-07T15:48:20.370932Z",
     "iopub.status.idle": "2024-05-07T15:48:21.344387Z",
     "shell.execute_reply": "2024-05-07T15:48:21.343460Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "graph = nx.erdos_renyi_graph(7, 0.6, seed=79)\n",
    "nx.draw_kamada_kawai(graph, with_labels=True)\n",
    "max_clique_model = define_max_clique_model(graph)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "abd17e36-857b-4101-9188-1be70206177e",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Setting Up the Classiq Problem Instance\n",
    "\n",
    "In order to solve the Pyomo model defined above, we use the Classiq combinatorial optimization engine. For the quantum part of the QAOA algorithm (`QAOAConfig`) - define the number of repetitions (`num_layers`):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "4233341d-139c-493b-b4af-210f71e3354a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-07T15:48:21.352378Z",
     "iopub.status.busy": "2024-05-07T15:48:21.350949Z",
     "iopub.status.idle": "2024-05-07T15:48:23.150678Z",
     "shell.execute_reply": "2024-05-07T15:48:23.150039Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "from classiq import construct_combinatorial_optimization_model\n",
    "from classiq.applications.combinatorial_optimization import OptimizerConfig, QAOAConfig\n",
    "\n",
    "qaoa_config = QAOAConfig(num_layers=20)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e8e4f132-55d7-4a46-846c-b4d4b5edac57",
   "metadata": {},
   "source": [
    "For the classical optimization part of the QAOA algorithm we define the maximum number of classical iterations (`max_iteration`) and the $\\alpha$-parameter (`alpha_cvar`) for running CVaR-QAOA, an improved variation of the QAOA algorithm [[3](#cvar)]:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "7384872d-a28f-49e3-918d-a5749c70d873",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-07T15:48:23.153812Z",
     "iopub.status.busy": "2024-05-07T15:48:23.153151Z",
     "iopub.status.idle": "2024-05-07T15:48:23.157294Z",
     "shell.execute_reply": "2024-05-07T15:48:23.156687Z"
    },
    "pycharm": {
     "name": "#%%\n"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "optimizer_config = OptimizerConfig(max_iteration=1, alpha_cvar=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "01c3df80-5e78-4cf6-9429-4ef0eaafed78",
   "metadata": {},
   "source": [
    "Lastly, we load the model, based on the problem and algorithm parameters, which we can use to solve the problem:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "3f848bc5-1ded-440a-b426-2f40e21949aa",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-07T15:48:23.160101Z",
     "iopub.status.busy": "2024-05-07T15:48:23.159651Z",
     "iopub.status.idle": "2024-05-07T15:48:23.462012Z",
     "shell.execute_reply": "2024-05-07T15:48:23.461349Z"
    },
    "pycharm": {
     "name": "#%%\n"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "qmod = construct_combinatorial_optimization_model(\n",
    "    pyo_model=max_clique_model,\n",
    "    qaoa_config=qaoa_config,\n",
    "    optimizer_config=optimizer_config,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4e28c1f5-d1df-4600-a364-0ef54dab8209",
   "metadata": {},
   "source": [
    "We also set the quantum backend we want to execute on:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "794a44cd-6d2a-47b1-9e71-fb2d05a8442b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-07T15:48:23.465067Z",
     "iopub.status.busy": "2024-05-07T15:48:23.464641Z",
     "iopub.status.idle": "2024-05-07T15:48:23.482772Z",
     "shell.execute_reply": "2024-05-07T15:48:23.482176Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "from classiq import set_execution_preferences\n",
    "from classiq.execution import ClassiqBackendPreferences, ExecutionPreferences\n",
    "\n",
    "backend_preferences = ExecutionPreferences(\n",
    "    backend_preferences=ClassiqBackendPreferences(backend_name=\"aer_simulator\")\n",
    ")\n",
    "\n",
    "qmod = set_execution_preferences(qmod, backend_preferences)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "1acdcc28-3101-4a80-9b36-87cd5780abbb",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-07T15:48:23.485247Z",
     "iopub.status.busy": "2024-05-07T15:48:23.484855Z",
     "iopub.status.idle": "2024-05-07T15:48:23.511694Z",
     "shell.execute_reply": "2024-05-07T15:48:23.511113Z"
    }
   },
   "outputs": [],
   "source": [
    "from classiq import write_qmod\n",
    "\n",
    "write_qmod(qmod, \"max_clique\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6e3057bc-33bc-4a2c-818e-b967598c2141",
   "metadata": {},
   "source": [
    "## Synthesizing the QAOA Circuit and Solving the Problem\n",
    "\n",
    "We can now synthesize and view the QAOA circuit (ansatz) used to solve the optimization problem:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "ad8e435d-4482-4d5f-ad53-886581d4fea0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-07T15:48:23.514439Z",
     "iopub.status.busy": "2024-05-07T15:48:23.513955Z",
     "iopub.status.idle": "2024-05-07T15:48:49.929603Z",
     "shell.execute_reply": "2024-05-07T15:48:49.928841Z"
    },
    "pycharm": {
     "name": "#%%\n"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Opening: https://platform.classiq.io/circuit/88ddbcbe-e798-4683-b7be-3052b1efec1a?version=0.41.0.dev39%2B79c8fd0855\n"
     ]
    }
   ],
   "source": [
    "from classiq import show, synthesize\n",
    "\n",
    "qprog = synthesize(qmod)\n",
    "show(qprog)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1f78ae22-4ab8-4890-ad74-227dedcbde75",
   "metadata": {},
   "source": [
    "We now solve the problem by calling the `execute` function on the quantum program we have generated:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "27afef0a-52a4-4930-8a3a-f509bd5956bd",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-07T15:48:49.934524Z",
     "iopub.status.busy": "2024-05-07T15:48:49.933310Z",
     "iopub.status.idle": "2024-05-07T15:48:56.641053Z",
     "shell.execute_reply": "2024-05-07T15:48:56.640136Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "from classiq import execute\n",
    "\n",
    "res = execute(qprog).result()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f4f0b68a-e56f-4d11-b9f8-fe3b9bdab697",
   "metadata": {
    "tags": []
   },
   "source": [
    "# Optimization Results"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bdacb755-5cdc-45c2-95d5-037efe20f9d6",
   "metadata": {},
   "source": [
    "We can also examine the statistics of the algorithm:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "0134df1a-8894-4a1f-b6da-dc1883a49599",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-07T15:48:56.653630Z",
     "iopub.status.busy": "2024-05-07T15:48:56.645232Z",
     "iopub.status.idle": "2024-05-07T15:48:56.764591Z",
     "shell.execute_reply": "2024-05-07T15:48:56.763847Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>probability</th>\n",
       "      <th>cost</th>\n",
       "      <th>solution</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>0.001</td>\n",
       "      <td>4.0</td>\n",
       "      <td>[0, 1, 1, 1, 0, 1, 0]</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>0.003</td>\n",
       "      <td>4.0</td>\n",
       "      <td>[1, 1, 1, 1, 0, 0, 0]</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>0.001</td>\n",
       "      <td>3.0</td>\n",
       "      <td>[0, 1, 0, 0, 0, 1, 1]</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>0.001</td>\n",
       "      <td>3.0</td>\n",
       "      <td>[1, 0, 0, 1, 1, 0, 0]</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>0.003</td>\n",
       "      <td>3.0</td>\n",
       "      <td>[0, 1, 1, 0, 0, 1, 0]</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     probability  cost               solution  count\n",
       "115        0.001   4.0  [0, 1, 1, 1, 0, 1, 0]      1\n",
       "90         0.003   4.0  [1, 1, 1, 1, 0, 0, 0]      3\n",
       "107        0.001   3.0  [0, 1, 0, 0, 0, 1, 1]      1\n",
       "111        0.001   3.0  [1, 0, 0, 1, 1, 0, 0]      1\n",
       "89         0.003   3.0  [0, 1, 1, 0, 0, 1, 0]      3"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "from classiq.applications.combinatorial_optimization import (\n",
    "    get_optimization_solution_from_pyo,\n",
    ")\n",
    "\n",
    "solution = get_optimization_solution_from_pyo(\n",
    "    max_clique_model, vqe_result=res[0].value, penalty_energy=qaoa_config.penalty_energy\n",
    ")\n",
    "optimization_result = pd.DataFrame.from_records(solution)\n",
    "optimization_result.sort_values(by=\"cost\", ascending=False).head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2724dafb-eb26-4756-8086-e415cecb0e78",
   "metadata": {},
   "source": [
    "## Resulting Clique"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "4d99764d-8ff1-4397-9dac-c5e584862bfb",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-07T15:48:56.769629Z",
     "iopub.status.busy": "2024-05-07T15:48:56.768261Z",
     "iopub.status.idle": "2024-05-07T15:48:57.012646Z",
     "shell.execute_reply": "2024-05-07T15:48:57.011984Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "solution = optimization_result.solution[optimization_result.cost.idxmax()]\n",
    "solution_nodes = [v for v in graph.nodes if solution[v]]\n",
    "solution_edges = [\n",
    "    (u, v) for u, v in graph.edges if u in solution_nodes and v in solution_nodes\n",
    "]\n",
    "nx.draw_kamada_kawai(graph, with_labels=True)\n",
    "nx.draw_kamada_kawai(\n",
    "    graph,\n",
    "    with_labels=True,\n",
    "    nodelist=solution_nodes,\n",
    "    edgelist=solution_edges,\n",
    "    node_color=\"r\",\n",
    "    edge_color=\"r\",\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d4d30ce4-f2b3-4049-b0e0-3cdc7b4897a1",
   "metadata": {},
   "source": [
    "And the histogram:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "c3233840-123c-4e29-8368-87ea3c135863",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-07T15:48:57.016876Z",
     "iopub.status.busy": "2024-05-07T15:48:57.015879Z",
     "iopub.status.idle": "2024-05-07T15:48:57.334652Z",
     "shell.execute_reply": "2024-05-07T15:48:57.333914Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<Axes: title={'center': 'cost'}>]], dtype=object)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "optimization_result.hist(\"cost\", weights=optimization_result[\"probability\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "896bd3ad-ac54-4e21-b654-ba00743ece86",
   "metadata": {},
   "source": [
    "Lastly, we can compare to the classical solution of the problem:"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c9b54c5b-10e5-4f9c-9e00-44ac2cf24a33",
   "metadata": {},
   "source": [
    "## Classical optimizer results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "dd5a1911-0eea-47fc-82f6-8942c8a4eac8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-07T15:48:57.339572Z",
     "iopub.status.busy": "2024-05-07T15:48:57.338409Z",
     "iopub.status.idle": "2024-05-07T15:48:57.474823Z",
     "shell.execute_reply": "2024-05-07T15:48:57.474130Z"
    },
    "pycharm": {
     "name": "#%%\n"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model unknown\n",
      "\n",
      "  Variables:\n",
      "    x : Size=7, Index=x_index\n",
      "        Key : Lower : Value                  : Upper : Fixed : Stale : Domain\n",
      "          0 :     0 :                    1.0 :     1 : False : False : Binary\n",
      "          1 :     0 :                    1.0 :     1 : False : False : Binary\n",
      "          2 :     0 :                    1.0 :     1 : False : False : Binary\n",
      "          3 :     0 :                    1.0 :     1 : False : False : Binary\n",
      "          4 :     0 :                    0.0 :     1 : False : False : Binary\n",
      "          5 :     0 : 3.9960192291414966e-08 :     1 : False : False : Binary\n",
      "          6 :     0 :                    0.0 :     1 : False : False : Binary\n",
      "\n",
      "  Objectives:\n",
      "    value : Size=1, Index=None, Active=True\n",
      "        Key  : Active : Value\n",
      "        None :   True : 4.0000000399601925\n",
      "\n",
      "  Constraints:\n",
      "    clique_constraint : Size=1\n",
      "        Key  : Lower : Body                  : Upper\n",
      "        None :   0.0 : 7.992038458282993e-08 :   0.0\n"
     ]
    }
   ],
   "source": [
    "from pyomo.opt import SolverFactory\n",
    "\n",
    "solver = SolverFactory(\"couenne\")\n",
    "solver.solve(max_clique_model)\n",
    "\n",
    "max_clique_model.display()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "5fccfe7a-4567-4c2c-8287-1cae1b75e875",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-07T15:48:57.479695Z",
     "iopub.status.busy": "2024-05-07T15:48:57.478528Z",
     "iopub.status.idle": "2024-05-07T15:48:57.808411Z",
     "shell.execute_reply": "2024-05-07T15:48:57.807685Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "solution = [int(pyo.value(max_clique_model.x[i])) for i in graph.nodes]\n",
    "solution_nodes = [v for v in graph.nodes if solution[v]]\n",
    "solution_edges = [\n",
    "    (u, v) for u, v in graph.edges if u in solution_nodes and v in solution_nodes\n",
    "]\n",
    "nx.draw_kamada_kawai(graph, with_labels=True)\n",
    "nx.draw_kamada_kawai(\n",
    "    graph,\n",
    "    with_labels=True,\n",
    "    nodelist=solution_nodes,\n",
    "    edgelist=solution_edges,\n",
    "    node_color=\"r\",\n",
    "    edge_color=\"r\",\n",
    ")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
